FG Neurotechnologie

Advances in signal processing push forward the Neurotechnology domain along with the Brain-Computer Interface (BCI) research which deals with the analysis of brain activity. Heading for a future that will most probably happen, where either healthy persons or people with disabilities communicate and control external devices without muscle control, a symbiotic relationship between humans and mach...

We provide a data set of a BCI study using a motor imagery paradigm. In a calibration session, participants were instructed by cues to perform different types of imagined movements. The pair of classes resulting in the most promising discrimination was chosen and a classifier was trained. That classifier was used in the feedback session to let the participants move a cursor horizontally accordi...

Objective: Decoding neurocognitive processes on a single-trial basis with Brain-Computer Interface (BCI) techniques can reveal the user's internal interpretation of the current situation. Such information can potentially be exploited to make devices and interfaces more user aware. In this line of research, we took a further step by studying neural correlates of different levels of cognitive pro...

EEG and behavioral data of seventeen participants recorded by members of the Neurotechnology Group at Technische Universität Berlin. Details of the study are published in "Nicolae I-E, Acqualagna L and Blankertz B. (2017). Assessing the Depth of Cognitive Processing as the Basis for Potential User-State Adaptation. Front. Neurosci. 11:548, 2017a. doi: https://doi.org/10.3389/fnins.2017.00548

Real-time assessment of mental workload from EEG plays an important role in enhancing symbiotic interaction of human operators in immersive environments. In this study we thus aimed at predicting the difficulty level of a video game a person is playing at a particular moment from the ongoing EEG activity. Therefore, we made use of power modulations in the theta (4–7 Hz) and alpha (8–13 Hz) freq...

The human factor plays the key role for safety in many industrial and civil every-day operations in our technologized world. Human failure is more likely to cause accidents than technical failure, e.g. in the challenging job of tugboat captains. Here, cognitive workload is crucial, as its excess is a main cause of dangerous situations and accidents while being highly participant and situation d...

Research on brain-computer interfacing (BCI) has demonstrated that specific brain activity patterns can be detected in the electroencephalogram (EEG) with multivariate methods from machine learning and signal processing in real-time. Objective. This direct access to the neural processes potentially provides an opportunity to learn about the users of technical applications in a novel way. In thi...

Advancements in machine learning in combination with fundamental research in cognitive neuroscience have put forth application areas for brain-computer interfaces (BCIs) that go beyond communication and control. The ability to decode covert mental states and intentions from the electroencephalogram (EEG) in real-time – hence, to study the "brain at work" – establishes the basis for multifaceted...

EEG and behavioral data of thirteen people were recorded by members of the Neurotechnology Group at Technische Universität Berlin. Details of the study are published in Wenzel M A, Almeida I and Blankertz B. Is Neural Activity Detected by ERP-based Brain-Computer Interfaces Task Specific? PLOS ONE. 2016. To appear.